\begin{table}

\caption{Regression Models: Heterogenous effects of the Deactivation conditional on Age  }
\centering
\begin{threeparttable}
\begin{tabular}[t]{lcccccc}
\toprule
  & False Rumors Exposure & True News  Exposure & False Rumors Accuracy & True News Accuracy & Polarization Index & Subjective Well-Being Index\\
\midrule
Treatment & -0.210 & -0.365* & -0.079 & -0.118 & -0.102 & -0.101\\
 & (0.199) & (0.161) & (0.203) & (0.199) & (0.403) & (0.636)\\
Age & -0.045 & -0.039 & 0.001 & 0.018 & 0.072 & 0.307\\
 & (0.060) & (0.046) & (0.057) & (0.059) & (0.118) & (0.192)\\
Treatment x Age & -0.097 & 0.039 & 0.003 & 0.043 & 0.011 & 0.152\\
 & (0.077) & (0.066) & (0.082) & (0.079) & (0.163) & (0.268)\\
\midrule
Num.Obs. & 660 & 660 & 660 & 660 & 660 & 660\\
R2 & 0.164 & 0.134 & 0.180 & 0.104 & 0.141 & 0.131\\
R2 Adj. & 0.122 & 0.091 & 0.139 & 0.060 & 0.098 & 0.088\\
RMSE & 0.94 & 0.79 & 1.01 & 0.98 & 1.99 & 3.33\\
\bottomrule
\multicolumn{7}{l}{\rule{0pt}{1em}+ p $<$ 0.1, * p $<$ 0.05, ** p $<$ 0.01, *** p $<$ 0.001}\\
\end{tabular}
\begin{tablenotes}
\item \textit{Note: } 
\item  Robust standard errors in Parentheses. All models use the Covariate-Adjusted ITT estimator. 
\end{tablenotes}
\end{threeparttable}
\end{table}
